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Development of ultra-high efficiency soft X-ray angle-resolved photoemission spectroscopy equipped with deep prior-based denoising method

Strongly Correlated Electrons 2026-03-05 v2 Materials Science

Abstract

Soft X-ray angle resolved photoemission spectroscopy (SX-ARPES) is one of the most powerful spectroscopic techniques to visualize the three-dimensional bulk electronic structure in reciprocal lattice space. Compared with ARPES employing low-energy photon sources, the time burden imposed by a lower photoelectron yield, stemming from the photoionization cross-section, has been a persistent technical challenge. To address this challenge, we have developed a noise removal system by using the deep prior-based method and integrated it into the micro focused SX-ARPES ({\mu}SX-ARPES) system at BL25SU in SPring-8. Our implemented system effectively eliminates the grid and spike noise typically present in ARPES data acquired using the voltage Fixed-mode, within about 30 seconds. We demonstrate, through the {\mu}SX-ARPES measurements on a single crystal of CeRu2Si2, that data with sufficient statistical accuracy can be obtained in approximately 40 seconds. In addition, we present the potential of high signal-to-noise ratio ARPES measurement, achieving an energy resolution of 51.6 meV at an excitation energy of 708 eV in {\mu}SX-ARPES measurements on polycrystalline gold. Our developed system successfully reduces the time burden in SX-ARPES and paves the way for advancements in lower photoelectron yield measurements, such as those requiring higher energy resolution and three-dimensional nonequilibrium measurements.

Keywords

Cite

@article{arxiv.2511.22909,
  title  = {Development of ultra-high efficiency soft X-ray angle-resolved photoemission spectroscopy equipped with deep prior-based denoising method},
  author = {Kohei Yamagami and Yuichi Yokoyama and Yuta Sumiya and Hayaru Shouno and Tetsuro Nakamura and Masaichiro Mizumaki},
  journal= {arXiv preprint arXiv:2511.22909},
  year   = {2026}
}

Comments

9 pages, 5 figures, 1 table